NVIDIA

DECEMBER 4, 2023

Since its 2018 launch, MLPerf , the industry-standard benchmark for AI, has provided numbers that detail the leading performance of NVIDIA GPUs on both AI training and inference. An AI model, also called a neural network, is essentially a mathematical lasagna, made from layer upon layer of linear algebra equations.

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Viso.ai

DECEMBER 3, 2023

The recent deep learning algorithms provide robust person detection results. However, deep learning models such as YOLO that are trained for person detection on a frontal view data set still provide good results when applied for overhead view person counting ( TPR of 95%, FPR up to 0.2% ).

Convolutional Neural Networks 98

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 98

Marktechpost

JULY 3, 2023

We will give details of Artificial Intelligence approaches such as Machine Learning and Deep Learning. By the end of the article, you will understand how innovative Deep Learning technology leverages historical data and accurately forecasts outcomes of lengthy and expensive experimental testing or 3D simulation (CAE).

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Mlearning.ai

APRIL 8, 2023

Over the years, we evolved that to solving NLP use cases by adopting Neural Network-based algorithms loosely based on the structure and function of a human brain. 2003) “ Support-vector networks ” by Cortes and Vapnik (1995) Significant people : David Blei Corinna Cortes Vladimir Vapnik 4.

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PyImageSearch

NOVEMBER 13, 2023

Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al.

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Mlearning.ai

MAY 5, 2023

It wasn’t until the development of deep learning algorithms in the 2000s and 2010s that LLMs truly began to take shape. Deep learning algorithms are designed to mimic the structure and function of the human brain, allowing them to process vast amounts of data and learn from that data over time.

Large Language Models 98

Large Language Models Neural Network Natural Language Processing Deep Learning 98

Flipboard

JULY 10, 2023

An autoencoder is an artificial neural network used for unsupervised learning tasks (i.e., Figure 5: Architecture of Convolutional Autoencoder for Image Segmentation (source: Bandyopadhyay, “Autoencoders in Deep Learning: Tutorial & Use Cases [2023],” V7Labs , 2023 ). What Are Autoencoders?

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Viso.ai

NOVEMBER 4, 2024

Convolutional deep learning models have been successfully used to forecast weather maps, according to recent studies. Deep learning models provide near-90% accuracy for both solar and wind location prediction, outperforming other conventional ML techniques. Lastly, the model in recurrent neural network techniques (e.g.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Deep Learning 52

Artificial Corner

SEPTEMBER 30, 2024

Subscribe now The New AI Approach in Healthcare In healthcare, neural networks are showing a lot of potential. Since 2018, the Da Vinci 5 robotic surgeon has been in use. Since the prosthetic uses AI, it continuously adapts to different environments and situations, getting better over time as it learns.

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Heartbeat

FEBRUARY 6, 2023

In the second step, these potential fields are classified and corrected by the neural network model. R-CNN (Regions with Convolutional Neural Networks) and similar two-stage object detection algorithms are the most widely used in this regard. YOLOv3 is a newer version of YOLO and was released in 2018.

Algorithm 90

Algorithm Convolutional Neural Networks Neural Network Computer Vision 90

Heartbeat

DECEMBER 8, 2023

He focused on generative AI trained on large language models, The strength of the deep learning era of artificial intelligence has lead to something of a renaissance in corporate R&D in information technology, according to Yann LeCun, chief AI. Hinton is viewed as a leading figure in the deep learning community.

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IBM Journey to AI blog

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. A foundation model is built on a neural network model architecture to process information much like the human brain does.

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Heartbeat

MARCH 14, 2023

Some of the methods used for scene interpretation include Convolutional Neural Networks (CNNs) , a deep learning-based methodology, and more conventional computer vision-based techniques like SIFT and SURF. It lets robots see and understand their surroundings, so they can do tasks and make choices on their own.

Computer Vision 97

Computer Vision Robotics Deep Learning Convolutional Neural Networks 97

Mlearning.ai

FEBRUARY 10, 2023

Addressing bias and Variance Here is the solution to address bias and variance problems: If you have a high avoidable bias; then it is recommended to use a bigger model i.e. a neural network with more hidden layers and hidden units. A more giant network and big data will improve the performance significantly. URL: htts://info.

Machine Learning 52

Machine Learning Neural Network Deep Learning Computer Vision 52

Mlearning.ai

MARCH 9, 2023

Recent studies have demonstrated that deep learning-based image segmentation algorithms are vulnerable to adversarial attacks, where carefully crafted perturbations to the input image can cause significant misclassifications (Xie et al., 2018; Sitawarin et al., 2018; Papernot et al., 2018; Papernot et al.,

Computer Vision 52

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Mlearning.ai

JANUARY 17, 2024

The foundations for today’s generative language applications were elaborated in the 1990s ( Hochreiter , Schmidhuber ), and the whole field took off around 2018 ( Radford , Devlin , et al.). Complex ML problems can only be solved in neural networks with many layers. Deep learning neural network.

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Viso.ai

JUNE 12, 2024

Our software helps several leading organizations start with computer vision and implement deep learning models efficiently with minimal overhead for various downstream tasks. Large Language Models – Source In 2018, OpenAI researchers and engineers published an original work on AI-based generative large language models.

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NVIDIA

OCTOBER 4, 2023

Harnessing the raw power of NVIDIA GPUs and aided by a network of thousands of cameras dotting the Californian landscape, DigitalPath has refined a convolutional neural network to spot signs of fire in real time. a short drive from the town of Paradise, where the state’s deadliest wildfire killed 85 people in 2018.

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Pickl AI

JULY 24, 2024

The advent of big data, coupled with advancements in Machine Learning and deep learning, has transformed the landscape of AI. Techniques such as neural networks, particularly deep learning, have enabled significant breakthroughs in image and speech recognition, natural language processing, and autonomous systems.

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AWS Machine Learning Blog

SEPTEMBER 23, 2024

Since its launch in 2018, Just Walk Out technology by Amazon has transformed the shopping experience by allowing customers to enter a store, pick up items, and leave without standing in line to pay. The following diagram illustrates the process. Chris Broaddus is a Senior Manager at AWS.

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Neural Network AI AI Algorithm 96

NVIDIA

DECEMBER 21, 2023

DigitalPath, based in Chico, California, has refined a convolutional neural network to spot wildfires. The mission is near and dear to DigitalPath employees, whose office sits not far from the town of Paradise, where California’s deadliest wildfire killed 85 people in 2018. We don’t want people to lose their lives.”

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Dlabs.ai

AUGUST 20, 2020

If you’re looking for the best free eBooks related to artificial intelligence, machine learning, or deep learning – this list is for you. Dive into Deep Learning Authors: Aston Zhang, Zack C. Smola The first eBook on our must-read list is a deep-dive into deep learning.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 52

Viso.ai

JULY 17, 2024

Image analogies patch-based texture in-filling for artistic rendering – source The field of Neural style transfer took a completely new turn with Deep Learning. With deep learning, the results were impressively good. 2018) StarGAN extends GANs to multi-domain image translation. Gatys et al.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

Viso.ai

JUNE 4, 2024

Our software helps several leading organizations start with computer vision and implement deep learning models efficiently with minimal overhead for various downstream tasks. Many of these methods utilize deep learning and Convolutional Neural Networks (CNNs) to create point cloud processing.

Computer Vision 52

Computer Vision Convolutional Neural Networks Deep Learning Neural Network 52

deepsense.ai

APRIL 16, 2023

This allows for the efficient processing of large amounts of data and can significantly reduce the time required for training deep learning models. The intermediate activations of the neural network are recomputed on-the-fly during the backward pass of the training process rather than storing them in memory during the forward pass.

Large Language Models 52

Large Language Models Neural Network Deep Learning Explainability 52

Heartbeat

MARCH 15, 2023

An open-source machine learning model called BERT was developed by Google in 2018 for NLP, but this model had some limitations, and due to this, a modified BERT model called RoBERTa (Robustly Optimized BERT Pre-Training Approach) was developed by the team at Facebook in the year 2019. Here’s a high-level overview of how it works.

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Lexalytics

APRIL 5, 2021

They were not wrong: the results they found about the limitations of perceptrons still apply even to the more sophisticated deep-learning networks of today. This book effectively killed off interest in neural networks at that time, and Rosenblatt, who died shortly thereafter in a boating accident, was unable to defend his ideas.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

AI Impacts

FEBRUARY 1, 2023

The alignment problem from a deep learning perspective. link] 8 From Hacker News user api: “To give a specific example: I once wrote an objective function to train an evolving system to classify images, a simple machine learning test. "The arXiv preprint arXiv:1803.03453 (2018). link] Published November 2, 2018.

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AI AI OpenAI Large Language Models 130

Towards AI

JULY 20, 2023

An additional 2018 study found that each SLR takes nearly 1,200 total hours per project. New research has also begun looking at deep learning algorithms for automatic systematic reviews, According to van Dinter et al. dollars apiece.

Data Extraction 75

Data Extraction NLP Natural Language Processing Automation 75

Mlearning.ai

MARCH 2, 2023

Conclusion: BERT as Trend-Setter in NLP and Deep Learning References I. Preliminaries: Transformers and Unsupervised Transfer Learning This section presents the most important theoretical background to understand BERT. Benchmark Results V. Contributions of BERT V.1 1 Impact V.2 3 Applications VI.

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Bugra Akyildiz

OCTOBER 6, 2024

Articles (Image is taken from Model Optimization Toolkit page from Tensorflow) Pruning Aware Training Pruning in deep learning refers to the process of removing unnecessary weights or neurons from a neural network to reduce its size and computational requirements while maintaining performance.

Neural Network 52

Neural Network Large Language Models Data Mining Big Data 52

Viso.ai

APRIL 25, 2024

Today’s boom in CV started with the implementation of deep learning models and convolutional neural networks (CNN). 2018) published their research titled MobileFaceNets. Pacal conducted a large-scale study with a total of 106 deep learning models. They used less than 1 million parameters.

Computer Vision 52

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Viso.ai

MAY 20, 2023

It requires several times cheaper hardware than other neural networks and can be trained much faster on small datasets without any pre-trained weights. Most algorithms use a convolutional neural network (CNN) to extract features from the image to predict the probability of learned classes.

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Algorithm Computer Vision Deep Learning Neural Network 52

Flipboard

AUGUST 25, 2023

Zhavoronkov has a narrower definition of AI drug discovery, saying it refers specifically to the application of deep learning and generative learning in the drug discovery space. The “deep learning revolution” — a time when development and use of the technology exploded — took off around 2014, Zhavoronkov said.

Machine Learning 123

Machine Learning AI AI Deep Learning 123

Heartbeat

JANUARY 29, 2024

It emphasizes fast convergence during the fine-tuning process and demonstrates the power of simple yet effective strategies in Meta-Learning. Memory-Augmented Neural Networks (MANNs) The path that led to Memory-Augmented Neural Networks started with conceptualizing the Neural Turing Machine (NTM).

Machine Learning 52

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Viso.ai

FEBRUARY 25, 2023

Vision Transformer (ViT) have recently emerged as a competitive alternative to Convolutional Neural Networks (CNNs) that are currently state-of-the-art in different image recognition computer vision tasks. No 2018 Oct BERT Pre-trained transformer models started dominating the NLP field. Date Model Description Vision Transformer?

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Viso.ai

JULY 9, 2024

NVIDIA in 2018 came out with a breakthrough Model- StyleGAN, which amazed the world for its ability to generate ultra-realistic and high-quality images. StyleGAN is GAN (Generative Adversarial Network), a Deep Learning (DL) model, that has been around for some time, developed by a team of researchers including Ian Goodfellow in 2014.

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